Congratulations! This is an exciting moment to begin building a new mobile app. Cross-platform frameworks have changed everything: thanks to them, developers can now ship performant apps across many platforms with a single codebase. Two of the biggest frameworks are Flutter and React Native, both with a ton of buzz around them. So what’s the right choice for your project?
We’re going to investigate the basic strategies to debug an application created with Unity, from logs to breakpoints, during the development stage. Once an app is in production we can switch to using Bugfender, and we’ll explain this too. To illustrate this tutorial we have created a custom app called The Bugfender Game, a variation of the popular Flappy Bird. Unity is a cross-platform game engine that gives users the ability to create games and experiences in 2D, 3D, VR and AR.
The first lesson you learn as you start to work around the DevOps field is that being optimistic is not a good virtue. While that might seem overly pessimistic, let me explain. We plan our architecture to fit our needs, deal with edge cases, scale our applications up and as wide as we see fit, and with all of that, we still always expect for the unexpected to happen. As engineers, we are expected to deal with that unexpected.
With the latest release of Helix QAC, the static code analysis tool continues to provide you with in-depth, high-quality compliance coverage for C and C++ coding languages. However, what makes Helix QAC 2021.1 notable is that it now offers complete support for many key coding standards. Here is an overview of the most impactful enhancements made to Helix QAC.
Product lifecycle management is all about the dynamics between requirements and their fulfilment (e.g., the ability to test and prove that a requirement is fully covered, as defined during the product planning phase). Understanding this relationship, and respecting it unconditionally, allows great products to achieve world-class quality and stability. For the majority of products, the combination of people, processes, and technology is triggering different forms of changes to the original plan.
Data integration has been around for decades in some form or fashion, as organizations are always looking for ways to combine their enterprise data and collect it in a centralized location. The most commonly used and dominant type of data integration is ETL (extract, transform, load). ETL first extracts data from one or more source systems, transforms it as necessary, and then loads it into a target warehouse or data lake.
What’s the fastest and easiest path towards powerful cloud-native analytics that are secure and cost-efficient? In our humble opinion, we believe that’s Cloudera Data Platform (CDP). And sure, we’re a little biased—but only because we’ve seen firsthand how CDP helps our customers realize the full benefits of public cloud.
You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. It’s a pie-in-the-sky statement that sounds great, right? And while you’d be forgiven for thinking that it might sound too good to be true, operational ML is, in fact, achievable and sustainable. You can get the very kind of ML you need to increase revenue and lower costs. To help teams work smarter and do things faster.
